Yudong Yao
Biographic Data
| ID | 7958533 |
|---|---|
| NAME | Yudong Yao |
| GIVEN NAMES | Yudong |
| FAMILY NAME | Yao |
| SIGNATURE | YAO Y |
| AFFILIATIONS | Stevens Institute of Technology |
| ORCID | 0000-0003-3868-0593 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 1 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Predicting depression by using a novel deep learning model and video-audio-text multimodal data
These results underscore the robustness and precision of the IMDD-Net, highlighting the importance of integrating local and global features across multiple modalities for accurate depression prediction
Aberrant degree centrality of functional brain networks in subclinical depression and major depressive disorder
Altered DC in the STG, MTG, IPL, and MFG were identified in depression groups. The DC values of these altered regions and their combinations presented good discriminative ability between HC, SD, and MDD. These findings could help to find effective biomarkers and reveal the potential mechanisms of depression
Annual Report on Financing Old Age Care in China (2017)
No prominent works on this page.
Annual Report on Financing Old Age Care in China (2017)
Aberrant degree centrality of functional brain networks in subclinical depression and major depressive disorder
Altered DC in the STG, MTG, IPL, and MFG were identified in depression groups. The DC values of these altered regions and their combinations presented good discriminative ability between HC, SD, and MDD. These findings could help to find effective biomarkers and reveal the potential mechanisms of depression
Predicting depression by using a novel deep learning model and video-audio-text multimodal data
These results underscore the robustness and precision of the IMDD-Net, highlighting the importance of integrating local and global features across multiple modalities for accurate depression prediction
Depression (economics (2 works) · Major depressive disorder (2 works) · Medicine (2 works) · Amygdala (1 works) · Archaeology (1 works) · Audiology (1 works) · Business (1 works) · Cardiology (1 works) · China (1 works) · Deep learning (1 works)